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  • 标题:Moral hazard, asset specificity, implicit bonding, and compensation: the case of franchising.
  • 作者:Wimmer, Bradley S. ; Garen, John E.
  • 期刊名称:Economic Inquiry
  • 印刷版ISSN:0095-2583
  • 出版年度:1997
  • 期号:July
  • 语种:English
  • 出版社:Western Economic Association International
  • 摘要:There is a large and growing interest in the structuring of compensation to deal with the moral hazard problem. Much of this literature treats various forms of income sharing, such as piece rates and sharecropping, as a means for a principal to provide incentives to an agent. This literature has been extended to the case of two-sided moral hazard where both parties to an exchange may shirk. Another mechanism to induce effort discussed in the literature is bonding, where workers post a bond that is forgone if effort is inadequate. Klein [1980] and Klein and Leffler [1981] treat the possibility of specific assets as constituting an implicit bond, where poor performance by a firm is penalized by bankruptcy and sale of assets at a loss.
  • 关键词:Franchises

Moral hazard, asset specificity, implicit bonding, and compensation: the case of franchising.


Wimmer, Bradley S. ; Garen, John E.


I. INTRODUCTION

There is a large and growing interest in the structuring of compensation to deal with the moral hazard problem. Much of this literature treats various forms of income sharing, such as piece rates and sharecropping, as a means for a principal to provide incentives to an agent. This literature has been extended to the case of two-sided moral hazard where both parties to an exchange may shirk. Another mechanism to induce effort discussed in the literature is bonding, where workers post a bond that is forgone if effort is inadequate. Klein [1980] and Klein and Leffler [1981] treat the possibility of specific assets as constituting an implicit bond, where poor performance by a firm is penalized by bankruptcy and sale of assets at a loss.

This paper studies a situation where these issues coalesce: the case of compensation arrangements in franchising. The typical franchise contract calls for the sharing of franchise income between franchisee and franchisor. Additionally, franchisees may be terminated for poor performance. If franchise assets have a degree of specificity, the ensuing sale of assets at a loss provides a penalty for poor performance.

We examine the determinants of franchise royalty rates and fees in this setting. While there is a literature on two-sided moral hazard and some empirical work on franchising based on this idea, none incorporates the potential influence of asset specificity. We explicitly consider the role of implicit bonding and asset specificity in conjunction with moral hazard on the part of both trading parties. We go beyond previous work in franchising by estimating the effects of asset specificity and other influences on the royalty rate. Further, part of our empirical work utilizes improved micro data on actual franchise contracts.

Our approach and its implications are discussed in section II. Consistent with previous work, we expect the royalty rate to decrease (increase) as the importance of the franchisee's (franchisor's) input increases. However, more specific capital, with the threat of termination, acts as an implicit bond and substitutes for a reduced royalty rate in inducing franchisee effort. Thus, we expect royalty rates to increase with asset specificity. Also, unlike other approaches, we do not necessarily expect an inverse relationship between the royalty rate and the franchise fee. For example, the greater the importance of franchisor effort the higher the royalty rate, but the franchise fee may also increase if franchise revenue rises by enough.

Our hypotheses are tested using two different data sets. An original, firm-level data set is taken from Federal Trade Commission (FTC)-required Uniform Franchise Offering Circulars (UFOC).(1) In addition, data are obtained from Bond's 1989 The Source Book of Franchise Opportunities.

The data are discussed and the results presented in section III. We find substantial support for our approach. For example, factors that increase the importance of the franchisee's effort, such as the number of employees supervised, lower the royalty rate and increase the franchise fee. Also, a reduction in the specificity of the franchisee's investment due to leasing lowers the royalty rate and raises the franchise fee.(2) Section IV summarizes our findings and concludes the paper.

II. THE APPROACH AND THE HYPOTHESES

The typical franchising contract consists of a two-part payment by the franchisee to the franchisor. The franchisee pays an up-front, nonrefundable franchisee fee and a continuing royalty payment, usually a percentage of sales. In return the franchisee receives the right to use the franchisor's brand-name capital and a method of operation. In addition, the franchisor provides on-going support to the franchisee. However, the franchisor maintains the right to unilaterally terminate the contract if the franchisor determines that the franchisee is not delivering a product consistent with the quality guaranteed by the brand name. Our goal is to explain variations in the royalty rate and franchise fee in this context.

Denote the franchise fee as F and the royalty as R. We follow the literature in recognizing (e.g., Rubin [1978]) that, because franchisors and franchisees provide inputs to the franchise, R will be set to account for the effect on both franchisee and franchisor incentives.(3) In particular, a greater (lower) R gives the franchisor (franchisee) more effort incentives because (s)he retains a larger share of the returns to effort.(4) Lafontaine [1992] and Sen [1993] find empirical support for the idea that moral hazard considerations contribute to explaining variations in royalty rates.(5)

In our work, we also recognize that implicit bonding plays a role in influencing the franchise payment structure.(6) Mathewson and Winter [1985] treat explicit bonding and its difficulties in franchising. In another context, Klein and Leffler [1981] argue that specific assets may constitute an implicit bond. If the owner of the specific assets goes out of business due to poor performance, the specific assets can be sold only at a loss, thus providing incentives to perform. Klein [1980] recognizes that this incentive mechanism may operate in franchising. Here, we explicitly incorporate how asset specificity creates an implicit bond and affects the use of the royalty rate to deal with two-sided moral hazard.(7) The simultaneous consideration of these issues makes our approach unique in the literature.

The potential of termination for poor performance generates the incentive of the implicit bond. If termination occurs, franchisees sell the assets for their salvage value. Assume the assets are purchased for I and have salvage value [Alpha]I, where [Alpha] [less than or equal to] 1. Thus, 1 - [Alpha] is the degree of asset specificity. The amount (1 - [Alpha])I is forgone if termination occurs and so is equivalent to a bond. Higher franchisee effort can improve performance and reduce the chances of termination. Thus, the more specific are franchise assets, the higher is the implicit bond and the greater is franchisee effort.

Note that under certain conditions asset specificity may have the opposite effect on franchisor effort incentives. Terminated franchise assets can be purchased for [Alpha]I but have value of at least I in the franchise system. Thus, there may be a temptation for franchisors to reduce their support to franchises to induce poor performance and termination. This way the franchisor might purchase the assets for [Alpha]I and redeploy them elsewhere within the franchise system for benefit I. How attractive this temptation is depends on the desire of the franchisor to maintain a good reputation and the ease of inducing termination. The point remains that, all else constant, greater asset specificity may reduce franchisor effort incentives.

In designing the franchise contract, the franchisor establishes a royalty rate ex-ante taking account of the above discussed ex-post incentives.(8) The wealth-maximizing choice of the royalty rate trades off franchisor and franchisee effort, i.e., a higher R raises the former and reduces the latter. A straightforward prediction of this approach, also found elsewhere in the literature, is that the greater is the franchisor's (franchisee's) marginal product of effort, the higher (lower) is the royalty rate. Asset specificity also plays a role. Greater asset specificity raises franchisee effort, making it optimal to use the royalty rate to generate more franchisor effort.(9) Thus, we predict asset specificity will raise royalty rates. This is a unique prediction in the literature.

Franchisor reputation has an ambiguous effect on the royalty rate in our approach. A better reputation may raise the marginal product of both parties and presumably also reduces the franchisor's incentive to wrongfully terminate franchises.(10)

Consider now effects on the franchise fee. In our approach, the franchise fee is a rent-transfer device, bringing the franchisee down to his or her reservation level of utility and having no allocative effects. An exogenous variable affects the franchise fee in two basic ways: (1) if it causes total franchise income to rise (fall), the franchise fee rises (falls); (2) if it causes the franchisee's share of franchise income, 1 - R, to rise (fall), the franchise fee rises (falls). These influences may reinforce or offset one another.

A increase in 1 - [Alpha], the specificity of the franchise assets, causes the royalty rate to rise and reduces the value of the franchise in the event of termination. Both tend to reduce the franchise fee. An increase in I, [Alpha] constant, increases the amount of specific investment thus tending to reduce the franchise fee. However, a greater investment raises total franchise income, increasing the fee. Its overall effect is ambiguous.

An increase in the marginal product of franchisee effort reduces the royalty rate and raises F. If the higher marginal product also is associated with a higher total product, franchise income is higher also causing F to rise. An increase in the marginal product of the franchisor's effort raises the royalty rate and so lowers the fee. However, if associated with a greater total product, thereby raising franchise income, this raises the fee. No clear prediction can be made. Interestingly, we do not find that the royalty rate and the franchise fee necessarily move in opposite directions, as some authors claim (Blair and Kaserman [1982] and Lafontaine [1992]). While factors that raise the royalty rate tend to lower the fee, there are other effects.

Franchisor reputation likely increases the revenue of the franchise directly, suggesting a higher fee. However, reputation has an unclear effect on the royalty rate, creating some ambiguity.

III. THE DATA AND EMPIRICAL TESTS

Data Description

To test the hypotheses discussed above, two data sets were compiled. Data from The Source Book of Franchise Opportunities, 1989 Edition by Robert E. Bond (the Bond data set) and an original data set gathered from FTC-required UFOC are used to construct variables that proxy the above described effects.

The Source Book is a publication that aids the prospective franchisee in the selection of a franchisor and contains a large number of observations covering a wide range of franchising activity.(11) Our sample is limited to franchisors based in the United States that rely primarily on royalty payments and franchise fees for revenue. Based on this criterion, and after deleting observations with missing data on key variables (see below), 528 observations remain and are included in the analysis.

A UFOC provides potential franchisees with detailed information on the franchise contract and certain aspects of the franchisor. The UFOC data was obtained through visits to the state of Indiana's Securities Department and a general mailing to franchisors.(12) In order to utilize information from both sources of data, UFOC franchises were matched to the Bond data set. The final UFOC data set includes 196 franchisors; 131 franchisors that were on file with the Indiana Securities Division during the period February 1990 to August 1990 and 65 franchisors from the general mailing.

The royalty payments are reported as the fraction of franchisee sales paid to the franchisor. Royalty payments typically include both a royalty rate and an advertising contribution, the latter to be used solely for advertising. The empirical analysis includes regressions that use the royalty rate by itself and the sum of the royalty rate and the advertising contribution, denoted the share, as dependent variables.(13,14) The franchise fee is the initial, nonrefundable payment made by the franchisee to the franchisor. Descriptions, means, and standard deviations of all variables, along with predictions for the independent variables, are found in Table I.

A unique feature of our approach is the expectation that an increase in a franchisee's asset-specific investment increases the royalty rate. The franchisee's initial investment, net of the franchise fee, measures the size of the franchisee's initial capital requirements and is available from both sources of data.(15) Franchisee investment, however, does not capture the investment's specificity. We include information about the "type" of structure that the franchisee is required to obtain in an attempt to proxy asset specificity. In the UFOC data, dummy variables indicating if franchisees are required to build or purchase a structure, are allowed to lease, or may run the franchise from their homes are included in the empirical analysis.(16)

The type of structure depends largely on the franchise and often includes features unique to the franchising operation. When the franchisor requires the franchisee to acquire a unique structure, any necessary remodeling of an existing structure requires a large degree of franchisee-specific modifications. We expect franchisees to build or purchase the structure when the investment is highly specific because the nonrenewal of a lease places a large capital loss on the franchisor (Smith and Wakeman [1985]). When leasing premises, franchisees are not under the burden to sell the capital should the franchising contract be terminated, and this implies a lower degree of asset specificity. When franchisees are allowed [TABULAR DATA FOR TABLE I OMITTED] to run the franchise out of their homes, the investment may be highly specific to the franchise but specificity is expected to be reduced by the lack of site specificity. Thus, a building requirement is expected to have a positive (negative) effect on the royalty rate (franchise fee) while working out of the home is expected to have the opposite effect, assuming that leasing is the omitted case. Additionally, a dummy variable identifying franchisees who lease capital equipment is included and should decrease (increase) the royalty rate (franchise fee).

The effects of the level of investment and its degree of specificity on royalties are examined by entering investment and its interactions with the structure-type dummies. Investment is expected to have a positive effect on the royalty rate, with the effect being larger the greater its specificity. Thus, the investment variable in the lease case is predicted to have a positive effect on the royalty rate. We expect the interaction of the building dummy with investment to be positive as specificity is greater in this case. The lack of site-specificity in the home case implies that there is no clear-cut prediction for the interaction of the home dummy with investment. In the franchise fee regressions, recall that there is no unambiguous prediction concerning the effect of investment on the franchise fee.

The Bond data set has less detail regarding the nature of the franchisee's investment. While the level of investment is available, we are able only to discern if the franchisee does not lease capital. A nonlease dummy variable is created to indicate this. It does not specify whether the franchisee must construct an outlet or may operate out of the home. The absence of leasing indicates an increase in asset specificity and so the nonlease dummy and its interaction with investment should raise the royalty rate and the lack of leasing itself should lower the franchise fee.

An important hypothesis of our approach and elsewhere in the literature is the effect of the franchisee's and franchisor's marginal products of effort on the terms of the franchise contract. The franchisee's marginal product of effort is proxied by the average number of employees and the productivity of each employee. Employee productivity is likely to be inversely related to the labor-capital ratio, proxied here by employees over investment. Accordingly, the royalty rate is predicted to be negatively related to the number of employees and positively related to the labor-capital ratio. The reverse holds for the franchisee fee.

Also, an increase in the duration of franchisee training suggests an increase in the marginal product of franchisee effort. However, to the extent that training is franchise specific, training also may proxy for the amount of the franchisee's investment in specific human capital. It follows that no unambiguous prediction can be made regarding the effect of training.

It is expected that an increase in the advertising contribution implies an increase in the importance of national brand-name capital and the franchisor's marginal product of effort. This effect is reinforced as the number of franchised outlets increase. We expect the size of the advertising contribution and number of outlets to be positively related with the royalty rate, but to have an ambiguous effect on the franchise fee.

We also account for other potential influences on the royalty rate and franchise fee. To control for horizontal free riding and geographic dispersion, we include a dummy variable indicating if the franchisee operates in a sector characterized by nonrepeat-purchase customers and the number of states franchised, respectively. The nonrepeat dummy follows Caves and Murphy's [1976] taxonomy.(17) The number of states franchised is expected to be positively related to the cost of franchisor inputs (see Rubin [1978], Brickley and Dark [1987], and Lafontaine [1992]).

We also include as control variables proxies for monitoring, risk, and reputation (see Lafontaine [1992]). Klein and Saft [1985] argue monitoring by franchisors is easier if franchisees are required to purchase inputs directly from the franchisor. This is proxied by dummy variables indicating the presence of a franchisee purchase requirement. As in Lafontaine [1992], we proxy the franchisor's reputation with the number of years the franchisor operated before franchising the system and the number of years the franchising system has been in operation. To measure risk, the coefficient of variation of sales was created for each industry using industry average sales data from Franchising in the Economy [U.S. Department of Commerce 1988, 1990] for the years 1976 through 1988.(18,19)

The Results. The empirical analysis consists of tobit estimates of the royalty rate and franchise fee on the variables described above and in Table I. The findings are shown in Table II for the UFOC data and Table III for the Bond data.

Consider first the findings regarding the proxies for asset specificity with the UFOC data in Table II. An increase in investment, holding the degree of asset specificity constant, is expected to increase the royalty rate. The investment variable, which corresponds to the lease case, is positive although insignificant. The effect of the building and home dummies is revealed by their coefficients and their interactions with investment. For the building case, the dummy is positive, as expected, and its interaction is negative, which is contrary to our expectations. Both are significant. Using the coefficients in column 1, the net effect is that the royalty rate is higher when the franchisee must build as long as investment is less than $1.77 million. This holds for 94% of our sample. For the home case, the dummy is negative and its interaction is positive, with both attaining significance. However, computing its net effect on the royalty rate with the coefficients of either column, we find it is negative for two-thirds of the sample. Additionally, the lease capital equipment dummy has a negative and significant effect. Overall, these results are in general agreement with our prior that an increase in the size of the franchisee's specific investment leads to a higher royalty rate.

We also expect that asset specificity lowers the franchise fee, but that total investment has an ambiguous effect. In the UFOC data, we find the effect of the building dummy in conjunction with its interaction is negative in both columns 3 and 4, as expected. Only the interaction is significant. Also, the lease capital equipment dummy has a positive effect, as predicted, but it is not significant. Working out of the home tends to reduce the fee, contrary to expectations, although its significance is not overly strong.

The Bond data set has less detailed proxies regarding asset specificity: only the nonlease dummy and the investment variables. Referring to Table III, the effect of the nonlease dummy variable, when combined with its interaction with investment, is positive and significant in the royalty rate equation, as expected. In the share equation, the interaction term is positive and significant, as expected, but the dummy is negative although not significant. The positive and significant coefficients for the interactions of nonlease and investment in both the royalty rate and share equations indicate that the royalty rate increases with the level of investment for franchisees [TABULAR DATA FOR TABLE II OMITTED] that do not lease. The investment variable itself is negative but insignificant. The prediction that investment matters less when the franchisee is allowed to lease capital holds.

Regarding the findings for the fee using the Bond data, the nonlease dummy is negative and significant and its interaction with investment is positive and significant. The former [TABULAR DATA FOR TABLE III OMITTED] is supportive of our approach while the latter is not.

The results regarding investment and its degree of asset specificity are broadly consistent with our approach. As in Lafontaine [1992], we find that both the royalty rate and franchise fee are affected by the size of the franchisee's capital requirements. However, the size and direction of this relationship depend on the type of investment made by the franchisee. While it is difficult to proxy the degree of asset specificity, our findings are consistent with the hypothesis that leasing reduces the degree of asset specificity and the size of the franchisee's implicit bond, inducing a lower royalty rate and higher fee.

As in Lafontaine [1992] and Sen [1993], our empirical analysis supports the hypothesis that the marginal product of both the franchisee's and franchisor's efforts are important determinants of the royalty rate. The coefficient on the number of employees is negative in the royalty rate and share equations for both data sets. It is significant, however, only for the UFOC data. The coefficients for the employees-investment ratio are positive and significant in all regressions reported. The advertising contribution coefficient is positive for both data sets, reaching statistical significance in only the UFOC data. The number of outlets franchised is positive, as expected, and significant in all the royalty rate and share regressions.

As predicted, an increase in the number of employees raises the franchise fee and a rise in the employee-investment ratio lowers it. Statistical significance is reached only with the Bond data set. While we have no predictions regarding the sign of the advertising or number of outlets variables in the franchise fee equation, the former is positive, although insignificant, in both data sets and the latter is negative and significant.

The training variable is negative in both data sets for the royalty rate regressions. A similar result is found for the share regressions, although statistical significance is low. In the fee regressions, training is positive and significant in all specifications reported. These results are consistent with a longer training period increasing the franchisee's marginal product of effort.

The remaining variables provide mixed results. The number of states franchised, proxy-ing geographic dispersion, is insignificant in all specifications reported. In the fee regressions, this variable is positive and significant for all specifications. The nonrepeat customer variable, proxying for horizontal free riding, has negative coefficients in the royalty rate and share regressions, but is significant for only the Bond data. The influence on the franchise fee tends to be negative and significant.

The results concerning the monitoring, reputation, and risk proxies are generally consistent with those of Lafontaine [1992] and Sen [1993]. Input purchase requirements tend to reduce the royalty rate and have little effect on the fee. An increase in the franchisor's experience tends to raise the royalty rate, and an increase in the years the franchise system has operated reduces the fee in some specifications. The coefficient of variation of sales tends to raise both the royalty rate and the fee, although significance is mixed.

IV. SUMMARY

The case of franchising is one where many of the elements of moral hazard models merge. Issues of two-sided moral hazard, bonding, and asset specificity all play a role. The typical franchise contract calls for the sharing of franchise income between franchisee and franchisor, thus the issue of the incentive effects of residual income claimancy arises. Additionally, franchisees may be terminated for poor performance. If franchise assets have a degree of specificity, the ensuing sale of assets at a loss provides a penalty for poor performance and acts as an implicit bond. Therefore, bonding plays a role in the franchise contract.

Our work examines the determinants of franchise royalty rates and fees in this setting. While there is a literature on two-sided moral hazard and some empirical work on franchising based on this idea, none incorporates the potential influence of asset specificity. We extend existing literature by considering how asset specificity and bonding interact with other determinants of incentive pay. Our empirical work tests the hypotheses of this approach with both previously used and new franchising data.

Many of our findings are consistent with the earlier work of Lafontaine [1992] and Sen [1993]. For example, we find that the franchisor's residual income claim - the royalty rate - rises (falls) as the importance of the franshisor's marginal product rises (falls). However, our work goes beyond this to show that asset specificity and implicit bonding play a significant role. More specific capital, with the threat of termination, acts as an implicit bond and substitutes for a reduced royalty rate in inducing franchisee effort. Thus, higher royalty rates emerge with greater asset specificity. The general implication is that if one party to an exchange posts a larger bond, this improves their incentives and allows enhancement of the other party's incentives through a larger residual income claim. Our empirical findings lead to the conclusion that incentive and bonding issues are important in the determination of the compensation of franchisees and franchisors.

The views expressed here are those of the authors and do not necessarily reflect those of the Federal Communications Commission. We are especially grateful to Frank Scott for many helpful discussions and much valuable input. Also, the anonymous referees were most helpful with numerous, detailed comments. We also wish to thank David Baucus, Mark Berger, Glenn Blomquist, Richard Jensen and the participants in the Applied Microeconomics Workshop at the University of Kentucky for helpful comments. We thank the Indiana Securities Division and Frank McCormick for help in data collection.

1. The Franchise Offering Circular discloses the franchise contract to franchisees, outlining the obligations of all parties.

2. Other features of franchising, such as the use of company-owned stores, are not examined here.

3. Other models have been put forth to explain sharing contracts, including downstream rent extraction (Blair and Kaserman [1982] and Schmidt [1994]), risk sharing (Cheung [1969] and Stiglitz [1974]), measurement costs (Barzel [1982] and Leffler and Rucker [1991]), and signaling (Gallini and Lutz [1992]). Lafontaine [1992] provides an overview of this literature.

4. Two-sided moral hazard has been formally modeled in a franchising context by Lal [1990] and Bhattacharyya and Lafontaine [1995]. Examples of other applications include Eswaran and Kotwal [1985], Carmichael [1983], Cooper and Ross [1985], and Mann and Wissink [1988].

5. Also, much empirical work on franchising finds that agency costs are important in determining the fraction of company-owned outlets. As examples, see Brickley and Dark [1987], Lafontaine [1992], Norton [1988], and Scott [1995]. Also, Martin [1988] examines risk in determining company ownership of stores.

6. The issue of bonding was first formally treated by Becker and Stigler [1974] and extended by Lazear [1979]. The infeasibility of bonding is important in the efficient wage literature. For reviews and assessments of this literature, see Carmichael [1990] and Lang and Kahn [1990].

7. Minkler and Park [1994] examine the effect of specificity on the vertical integration of franchises.

8. This assumes that there are noncontractable aspects to both parties' efforts.

9. As noted previously, greater specificity also may reduce franchisor effort, so the royalty rate is raised to offset this.

10. Some have argued that, because a better reputation raises sales, the franchisor can charge a higher royalty rate (Blair and Kaserman [1982]). Our analysis implies that this need not be true as changing the royalty rate distorts incentives. In the context of a life-cycle model, Mathewson and Winter [1985] show that established (and presumably more reputable) franchises can have a higher royalty rate and a higher fee.

11. Sen [1993] and Scott [1995] also use data from The Source Book.

12. Indiana Disclosure Law IC 23-2-2.5 requires franchisors who wish to operate in Indiana to register and file a UFOC with the state. Franchises who meet equity requirements are exempt. To supplement the Indiana data, a general mailing was sent to franchisors requesting a UFOC. A response rate of 12.88% was obtained from the general mailing. For more details regarding the Uniform Franchise Offering Circular, see Wimmer [1992].

13. The UFOCs report, for some franchises, that the royalty rate may vary over time or with franchisee sales. Dummy variables were created for each of these cases and were included in specifications of the model not reported. Their coefficients proved to be insignificant while not affecting the other results. For the Bond data, when a range of royalty rates is reported, the average is used.

14. The share variable is used by Lafontaine [1992] and Sen [1993]. The model is tested using the advertising contribution as a part of the royalty payment and as an independent variable that proxies the franchisor's marginal product of effort.

15. Lafontaine [1992] uses initial capital requirements to proxy franchisor credit constraints.

16. The home case is a situation where franchisees may run the franchise out of their home or may obtain separate premises to run the business.

17. Caves and Murphy [1976] posit that repeat purchases are unimportant in the restaurant, automobile rental and the hotel, motel, and campground sectors.

18. For use of a similar variable, see Martin [1988], Norton [1988], and Lafontaine [1992].

19. In the UFOC franchise fee regressions, the length of the franchise contract, dummy variables indicating the presence of a lifetime franchise contract and a franchise fee that varies according to market size are included. For the Bond data set, only a contract length variable is available. These variables influence the present value of franchisee's expected income but not effort incentives.

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Bradley S. Wimmer: Industry Economist, Federal Communications Commission, Washington, D.C. Phone 1-202-418-1847, Fax 1-202-418-1567 E-mail bwimmer@fcc.gov

John E. Garen: Professor, University of Kentucky, Lexington Phone 1-606-257-3581, Fax 1-606-323-1920 E-mail jgaren@pop.uky.edu
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